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Do US Circuit Courts' decisions on criminal appeals influence sentence lengths imposed by US District Courts? This Element explores the use of high-dimensional instrumental variables to estimate this causal relationship. Using judge characteristics as instruments, this Element implements two-stage models on court sentencing data for the years 1991 through 2013. This Element finds that Democratic, Jewish judges tend to favor criminal defendants, while Catholic judges tend to rule against them. This Element also finds from experiments that prosecutors backlash to Circuit Court rulings while District Court judges comply. Methodologically, this Element demonstrates the applicability of deep instrumental variables to legal data.
This book provides an interdisciplinary overview of international human rights issues, offering truly international coverage including the Global South. Considering the philosophical foundations of human rights, Chen and Renteln explore the interpretive difficulties associated with identifying what constitute human rights abuses, and evaluate various perspectives on human rights. This book goes on to analyze institutions that strive to promote and enforce human rights standards, including the United Nations system, regional human rights bodies, and domestic courts. It also discusses a wide variety of substantive human rights including genocide, torture, capital punishment, and other cruel and unusual punishments. In particular, the book offers an accessible introduction to key understudied topics within human rights, such as socioeconomic rights, cultural rights, and environmental rights. It also focuses on the rights of marginalized groups, including children's rights, rights of persons with disabilities, women's rights, labor rights, indigenous rights, and LGBTQ+ rights, making this an engaging and invaluable resource for the contemporary student.
The linguistic study of Chinese, with its rich morphological, syntactic and prosodic/tonal structures, its complex writing system, and its diverse socio-historical background, is already a long-established and vast research area. With contributions from internationally renowned experts in the field, this Handbook provides a state-of-the-art survey of the central issues in Chinese linguistics. Chapters are divided into four thematic areas: writing systems and the neuro-cognitive processing of Chinese, morpho-lexical structures, phonetic and phonological characteristics, and issues in syntax, semantics, pragmatics, and discourse. By following a context-driven approach, it shows how theoretical issues in Chinese linguistics can be resolved with empirical evidence and argumentation, and provides a range of different perspectives. Its dialectical design sets a state-of-the-art benchmark for research in a wide range of interdisciplinary and cross-lingual studies involving the Chinese language. It is an essential resource for students and researchers wishing to explore the fascinating field of Chinese linguistics.
Body posture determination methods have many applications, including product design, ergonomic workplace design, human body simulation, virtual reality, and animation industry. Initiated in robotics, inverse kinematic (IK) method has been widely applied to proactive human body posture estimation. The analytic inverse kinematic (AIK) method is a convenient and time-saving type of IK methods. It is also indicated that, based on AIK methods, a specific body posture can be determined by the optimization of an arbitrary objective function. The objective of this paper is to predict the postures of human arms during reaching tasks. In this research, a human body model is established in MATLAB, where the middle rotation axis analytic kinematic method is accomplished, based on this model. The joint displacement function and joint discomfort function are selected to be initially applied in this AIK method. Results show that neither the joint displacement function nor the joint discomfort function predicts postures that are close enough to natural upper limb postures of human being, during reaching tasks. Therefore, a bi-criterion objective function is proposed by integrating the joint displacement function and joint discomfort function. The accuracy of the arm postures, predicted by the proposed objective function, is the most satisfactory, while the optimal value of the coefficient, in the proposed objective function, is determined by golden section search.
When designing programs to assist the poor, it is important to recognize who is most in need of government assistance. Although measures of poverty are often based on income alone, poverty measures based on both income and assets provide greater precision in the analysis of this group since accumulated assets can be liquidated to compensate for temporary shortfalls in income. The current study used the Panel Study of Income Dynamics (2007–2017) to analyze associations between different facets of poverty dynamics (i.e. poverty entry and exit) and its determinants. We explored differences in results based on whether poverty was measured by income alone, or income plus assets. The Cox proportional hazard regression was used to examine how demographic characteristics predicted poverty entry and poverty exit. Results indicated factors predicting poverty entry were not identical to those predicting difficulty of exiting poverty. Also, the risk of poverty entry and exit differed based on whether poverty was measured by income alone, or income plus assets. Thus, using income plus assets provides new perspectives into poverty dynamics which past research, based on income alone, did not provide. These new insights can be used to inform decisions about policies for poverty prevention and alleviation.
It has been suggested that psychosocial factors are related to survival time of inpatients with cancer. However, there are not many studies examining the relationship between spiritual well-being (SWB) and survival time among countries. This study investigated the relationship between SWB and survival time among three East Asian countries.
This international multicenter cohort study is a secondary analysis involving newly admitted inpatients with advanced cancer in palliative care units in Japan, South Korea, and Taiwan. SWB was measured using the Integrated Palliative Outcome Scale (IPOS) at admission. We performed multivariate analysis using the Cox proportional hazards model to identify independent prognostic factors.
A total of 2,638 patients treated at 37 palliative care units from January 2017 to September 2018 were analyzed. The median survival time was 18.0 days (95% confidence interval [CI] 16.5–19.5) in Japan, 23.0 days (95% CI 19.9–26.1) in Korea, and 15.0 days (95% CI 13.0–17.0) in Taiwan. SWB was a significant factor correlated with survival in Taiwan (hazard ratio [HR] 1.27; 95% CI 1.01–1.59; p = 0.04), while it was insignificant in Japan (HR 1.10; 95% CI 1.00–1.22; p = 0.06), and Korea (HR 1.02; 95% CI 0.77–1.35; p = 0.89).
Significance of results
SWB on admission was associated with survival in patients with advanced cancer in Taiwan but not Japan or Korea. The findings suggest the possibility of a positive relationship between spiritual care and survival time in patients with far advanced cancer.
Business process management (BPM) has been the main driver behind company optimization and operational efficiency. However, the digitization era we live in necessitates that organizations be agile and adaptable. Delivering unprecedented rates of automation-fueled agility is necessary to be a part of this digital revolution. On the other hand, BPM automation cannot be done only by concentrating on procedure space and traditional planning methodologies. With the introduction of BPM, where the deployment of BPM with cloud computing has undergone enormous development lately, cloud computing has been considered a particularly active topic of study. Cloud computing points to the provision of dependable computing environments based on improved infrastructure availability and service quality without imposing a significant cost load. This research aims to discover the relationship between technical factors, financial factors, environmental factors, security of the cloud-based information systems, and the agile development of industrial BPM (IBPM). The present study aims to fill this gap and show how partial least squares structural equation modeling (SEM) can be employed in this field. Importance–performance map analysis (IPMA) evaluated the importance and performance of factors in the SEM. IPMA enables the identification of factors with relatively low performance but relatively high importance in shaping dependent variables. The empirical findings showed that four key factors (technical, financial, environmental, and security) positively influence the agile development of IBPM.
Quality assurance and enhancement exercises are important in higher education. Curriculum assurance and enhancement exercise, relied in the past primarily on raw assessment data and self-reported, which lacked follow-up mechanisms gauging its effectiveness. This paper reports on an impact study of a curriculum review exercise using both digitalised data and self-reported data. Both the original review and its impact study were conducted on an English Programme in a Hong Kong university taken by around 6,000 students each year. Both adopted a learning analytics approach with digitalised behavioural and assessment data. Results of the impact study, which is the focus of this paper, demonstrate the strength of using learning analytics, including its capability of inter-course and intra-course investigations. Learning analytics can also empirically confirm and/or refute concerns reported by teachers and students. The use of digitalised data for learning analytics offers opportunities to implement and follow-up on quality assurance measures.
Maternal experiences of childhood adversity can increase the risk of emotional and behavioural problems in their children. This systematic review and meta-analysis provide the first narrative and quantitative synthesis of the mediators and moderators involved in the link between maternal childhood adversity and children's emotional and behavioural development. We searched EMBASE, PsycINFO, Medline, Cochrane Library, grey literature and reference lists. Studies published up to February 2021 were included if they explored mediators or moderators between maternal childhood adversity and their children's emotional and behavioural development. Data were synthesised narratively and quantitatively by meta-analytic approaches. The search yielded 781 articles, with 74 full-text articles reviewed, and 41 studies meeting inclusion criteria. Maternal mental health was a significant individual-level mediator, while child traumatic experiences and insecure maternal–child attachment were consistent family-level mediators. However, the evidence for community-level mediators was limited. A meta-analysis of nine single-mediating analyses from five studies indicated three mediating pathways: maternal depression, negative parenting practices and maternal insecure attachment, with pooled indirect standardised effects of 0.10 [95% CI (0.03–0.17)), 0.01 (95% CI (−0.02 to 0.04)] and 0.07 [95% CI (0.01–0.12)], respectively. Research studies on moderators were few and identified some individual-level factors, such as child sex (e.g. the mediating role of parenting practices being only significant in girls), biological factors (e.g. maternal cortisol level) and genetic factors (e.g. child's serotonin-transporter genotype). In conclusion, maternal depression and maternal insecure attachment are two established mediating pathways that can explain the link between maternal childhood adversity and their children's emotional and behavioural development and offer opportunities for intervention.
COVID-19 is erupting globally and Wuhan successfully controlled it within a month. Infections arose from infectious persons outside hospitals. After data revision, data-based and model-based analyses are implemented and the conclusions are as follows. The incubation period of most infected people may be 6-7 days. The number of infectious persons outside hospitals in Wuhan on Jan.20 is about 10000 and reached more than 20000 on the day of Lockdown, it exceeded 72000 on Feb.4. Both data-based and model-based analyses gave out the evolution of the reproduction number, which is over 2.5 in early January, then go down to 1.62 in late January and 1.20 in early February, a sudden drop to less than 0.5 due to the strict Stay-at-home management after Feb.11. Strategies of Stay-at-home, Safe-protective measures and Ark hospitals are the main contributions to control COVID-19 in Wuhan. Two inflection points of COVID-19 in Wuhan exactly correspond to Feb.5 and Feb.15, the two days when Ark hospitals were introduced and the complete implementation of Stay-at-home. Based on the expression of the reproduction number, group immunity also is discussed. It shows that only when the group immunization rate is over 75 percent can COVID-19 be under control, group immunity actually would be full infection and the total deaths will be 220,000 for a city as big as Wuhan. Sensitivity analysis suggests that 30 percent of people staying at home in combination with better behavior changes, such as social-distancing and frequent hand-washing, can effectively contain COVID-19. But only when this proportion is over 60 percent can the control effect and efficiency like Wuhan be obtained.
Emotionally unstable personality disorder (EUPD) accounts for up to 20% of diagnoses in the inpatient psychiatry population. The assessment, diagnosis, and treatment of any personality disorder may be challenging, and its classification remains debatable. Here I will describe a case of a dual diagnosis of EUPD and schizotypal personality disorder. Through the case report I will also reflect on my first experience of working with a patient with personality disorder, as a Psychiatry Foundation Fellowship doctor with little previous exposure to the psychiatry specialty.
The patient was a female in her thirties, previously diagnosed with EUPD, who had not benefitted from a number of psychological treatments. She had a history of suicidal behaviour and previous admissions but presented differently this time. She had short hair that was dyed in a vivid colour, was paranoid that she was being spied upon from an alternative universe and had suicidal plans to join the alternative universe. She also had auditory and visual hallucinations. On exploration it became apparent that she had similar episodes in the past, each lasting no more than a day. An additional diagnosis of schizotypal personality disorder was made, and she responded well to risperidone. Unfortunately, she was transferred to another ward for bed management reasons, whereupon the diagnosis reverted to EUPD and antipsychotics were stopped.
This case highlights how in mixed personality disorders, features of one personality disorder may be more predominant than another at different times. It also contradicts the notion that people with schizotypal personality disorder rarely present to mental health services. The inconsistency of diagnosis and lack of continuity of care caused immense distress to the patient, prolonging the acute episode. This highlights the importance of a good formulation in order to tailor care for the patient.
As a newly qualified doctor, working with patients with personality disorders was a meaningful experience. Through ward rounds and the seemingly trivial conversations along the corridor, I thought about the effect of transference and countertransference for the first time, which is applicable to any interpersonal interaction. I witnessed the harm caused by the lack of continuity of care. I reflected on the intricate balance between the advantage of establishing a diagnosis for the patient, and the drawback of the diagnosis leading to labelling. It made me face the stereotypes I held and allowed me to learn about the patient as an individual.
N-acetylcysteine (NAC) possesses a strong capability to ameliorate high-fat diet (HFD)-induced nonalcoholic-fatty liver disease (NAFLD) in mice, but the underlying mechanism is still unknown. Our study aimed to clarify the involvement of long noncoding RNAs (lncRNAs) in the beneficial effects of NAC on HFD-induced NAFLD. C57BL/6J mice were fed a normal-fat diet (10 % fat), a HFD (45 % fat), or a HFD plus NAC (2 g/L in the drinking water). After 14-week of intervention, NAC obviously rescued the deleterious alterations induced by HFD, including the changes in body and liver weights, hepatic triglycerides (TGs), plasma alanine aminotransferase (ALT), plasma aspartate transaminase (AST), and liver histomorphology (H&E and Oil red O staining). Through whole-transcriptome sequencing, 52167 (50758 known and 1409 novel) hepatic lncRNAs were detected. Our cross-comparison data revealed the expression of 175 lncRNAs were significantly changed by HFD but reversed by NAC. Five of those lncRNAs, lncRNA-NONMMUT148902.1 (NO_902.1), lncRNA-XR_001781798.1 (XR_798.1), lncRNA-NONMMUT141720.1 (NO_720.1), lncRNA-XR_869907.1 (XR_907.1), and lncRNA-ENSMUST00000132181 (EN_181) were selected based on an absolute log2 fold change (FC) value of greater than 4, P-value < 0.01, and P-adjusted value < 0.01. Further qRT-PCR analysis showed that the levels of lncRNA-NO_902.1, lncRNA-XR_798.1, and lncRNA-EN_181 were dramatically decreased by HFD but restored by NAC, consistent with the RNA-sequencing. Finally, we constructed a ceRNA network containing lncRNA-EN_181, 3 miRNAs, and 13 mRNAs, which was associated with the NAC-ameliorated NAFLD. Overall, lncRNA-EN_181 might be a potential target in NAC-ameliorated NAFLD. This finding enhanced our understanding of the biological mechanisms underlying the beneficial role of NAC.
Drawing on social learning theory and taking a motivational perspective, this study mainly investigates how leader humility can promote employees' other-oriented motivations, and uncovers the other-serving motivational mechanism through which leader humility can impact their employees' different types of voice behavior. By collecting data from 152 leader–subordinate dyads through an online survey, the results revealed that leader humility was positively related to both employees' prosocial motivation and organizational concern motivation. Meanwhile, these two motivations play mediating roles in explaining how leader humility can positively affect employees' supportive voice and challenging voice. It is noteworthy that leader humility, which features highlighting the value and strength of others, is more likely to trigger employees' prosocial motivation and thus influence their voice behavior. This research extends our understanding of leader humility, employee motivation, and workplace voice. Practical implications and limitations of the results are also discussed.
The impacts of training image sizes and optimizers on deep convolutional neural networks for weed detection in alfalfa have not been well explored. In this research, AlexNet, GoogLeNet, VGGNet, and ResNet were trained with various sizes of input images, including 200 × 200, 400 × 400, 600 × 600, and 800 × 800 pixels, and deep learning optimizers including Adagrad, AdaDelta, Adaptive Moment Estimation (Adam) and Stochastic Gradient Descent (SGD). Increasing input image sizes reduced the classification accuracy of all neural networks. The neural networks trained with the input images of 200 × 200 pixels resulted in better classification accuracy than the other image sizes investigated here. The optimizers affected the performance of the neural networks for weed detection. AlexNet and GoogLeNet trained with AdaDelta and SGD outperformed Adagrad and Adam; VGGNet trained with AdaDelta outperformed Adagrad, Adam, and SGD; and ResNet trained with AdaDelta and Adagrad outperformed the Adam and SGD. When the neural networks were trained with the best-performed input image size (200 × 200 pixels) and the deep learning optimizer, VGGNet was the most effective neural network with high precision and recall values (≥0.99) in the validation and testing datasets. At the same time, ResNet was the least effective neural network for classifying images containing weeds. However, the detection accuracy did not differ between broadleaf and grass weeds for the different neural networks studied here. The developed neural networks can be used for scouting weed infestations in alfalfa and further integrated into the machine vision subsystem of smart sprayers for site-specific weed control.